| rganization = config['openai']['organization_id'].strip('"').strip("'") | |
| ENGINE = config['openai']['engine'].strip('"').strip("'") | |
| prompt_config = { | |
| 'engine': ENGINE, | |
| 'temperature': TEMPERATURE, | |
| 'max_tokens': MAX_TOKENS, | |
| 'shell': SHELL, | |
| 'multi_turn': MULTI_TURN, | |
| 'token_count': 0 | |
| } | |
| return PromptFile(PROMPT_CONTEXT.name, prompt_config) | |
| def is_sensitive_content(content): | |
| """ | |
| Check if the content contains sensitive content | |
| Refer to https://beta.openai.com/docs/engines/content-filter for explanation | |
| """ | |
| if len(content) == 0: | |
| return False | |
| response = openai.Completion.create( | |
| engine="content-filter-alpha", | |
| prompt = "<|endoftext|>"+content+"\n--\nLabel:", | |
| temperature=0, | |
| max_tokens=1, | |
| top_p=0, | |
| logprobs=10 | |
| ) | |
| output_label = response["choices"][0]["text"] | |
| # This is the probability at which we evaluate that a "2" is likely real | |
| # vs. should be discarded as a false positive | |
| toxic_threshold = -0.355 | |
| if output_label == "2": | |
| # If the model returns "2", return its confidence in 2 or other output-labels | |
| logprobs = response["choices"][0]["logprobs"]["top_logprobs"][0] | |
| # If the model is not sufficiently confident in "2", | |
| # choose the most probable of "0" or "1" | |
| # Guaranteed to have a confidence for 2 since this was the selected token. | |
| if logprobs["2"] < toxic_threshold: | |
| logprob_0 = logprobs.get("0", None) | |
| logprob_1 = logprobs.get("1", None) | |
| # If both "0" and "1" have probabilities, set the output label | |
| # to whichever is most probable | |
| if logprob_0 is not None and logprob_1 is not None: | |
| if logprob_0 >= logprob_1: | |
| output_label = "0" | |
| else: | |
| output_label = "1" | |